GREAT: Generalized Reservoir Sampling based Triangle Counting Estimation over Streaming Graphs
Summary: GRS: generalized reservoir sampling that stores fewer edges yet yields uniform random edge samples in streaming graphs, cutting memory and compute vs fixed-size samplers. GREAT estimates triangle counts using GRS; GREAT+ reweights sampling for timestamp-interval distributions, giving ≈10× lower relative error. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Siyue Wu (Shenzhen University)
- 2. Dingming Wu (Shenzhen University)
- 3. Sinhong Cheuk (Shenzhen University)
- 4. Tsz Nam Chan (Shenzhen University)
- 5. Kezhong Lu (Shenzhen University)
BibTeX Citation
@article{wu_vldb25,
title = {{GREAT: Generalized Reservoir Sampling based Triangle Counting Estimation over Streaming Graphs}},
author = {Wu, Siyue and Wu, Dingming and Cheuk, Sinhong and Chan, Tsz Nam and Lu, Kezhong},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {7},
pages = {2031--2043},
doi = {10.14778/3734839.3734842},
url = {https://doi.org/10.14778/3734839.3734842},
year = {2025}
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 149 | New Sampling-Based Summary Statistics for Improving Approximate Query Answers | 1998 | SIGMOD | 0.00029226907 |
| 458 | Counting Triangles in Data Streams | 2006 | PODS | 0.0001810876 |
| 1,103 | Counting and Sampling Triangles from a Graph Stream | 2013 | VLDB | 0.000121583 |
| 2,635 | Sliding Window-based Approximate Triangle Counting over Streaming Graphs with Duplicate Edges | 2021 | SIGMOD | 8.3200595e-05 |
| 2,753 | Sampling Time-Based Sliding Windows in Bounded Space | 2008 | SIGMOD | 8.1647557e-05 |
| 4,500 | Approximately Counting Triangles in Large Graph Streams Including Edge Duplicates with a Fixed Memory Usage | 2018 | VLDB | 6.6603827e-05 |
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